Sequences of pictures may occupy vast amounts of storage space when represented in digital form. For example, suppose pictures in a sequence are digitized as discrete fields with 360 picture elements/horizontal line and 243 lines/field. Assuming the picture sequence is in color, a three-color separation may be used for each picture. If each color component is sampled at a 360×243 resolution with 8-bit/component precision, each picture could occupy approximately 262 Kbytes. If the moving pictures are sent uncompressed at 60 pictures per second, the raw data rate for the sequence may be about 126 Mbits/second. A one-minute video clip could occupy about 945 Mbytes.
Consider a point-of-sale surveillance system that may need to store sixty days' or more worth of data for later retrieval and display. Such a system may have a multitude of color video sources as well as other related data to store. If such a system had 32 color cameras, then it may require over 2.6 Peta bytes (or over 35,600 73 Gbyte disc drives) to store 60 days of data.
Analog Devices of Norwood, MA offers an IC chip product that will perform lossy spatial compression on individual camera fields for the purpose of reducing the amount of data needed to represent each discrete image. Also, they suggested that if further compression is needed for surveillance purposes, then further techniques to increase compression may need to be developed. They performed a software experiment whose results where documented on Jan. 15, 1998 and titled “ADPCM Coding Experiment-I” by Hakan Civi. This experiment is said to have employed basic pixel subtraction to determine the difference between two successive fields along with some kind of reconstructed-field feedback mechanism to deal with rounding in their pixel calculations (note: the Analog Devices document is not specific as to the details of the algorithm that was used, but the above described basics of their ADPCM approach were gleaned from conversations with Analog Devices). The Analog Devices' experiment was a software-only endeavor, and did not achieve the dramatic temporal compression results that were needed.
What is needed is a way to more efficiently compress a multitude of video signals real-time so that systems such as retail store surveillance systems may store the video signals for future retrieval at a reasonable system size and cost.